Student Name: Aisha Shoaib
Research Topic: A Framework for Multiple Damage Detection in structures using AI Techniques
Research Interests: Artificial Intelligence, Structural Health Monitoring
Supervisor: Dr. Ummul Baneen
Current Progress: In-process
Description
Engineering structures are designed to sustain longer however, these are susceptible to damage due to the changes in load characteristics, environmental effects, random loading and deterioration with time. The damage may lead to failure of structures which may bring about both human life and economic loss. Detecting, locating and quantifying the structural damage have remained a constant challenge for researchers and engineers. In recent years, use of computational intelligence techniques like ANN and algorithms for optimization have proven to be effective in identifying the severity of damage hence gained attention among researchers. ANNs is an artificial intelligence based technique that has capability to process the logical operations and can manage to adapt to nonlinear mapping, in complex problems or scenarios. The basic operation of ANNs is consisting of the prediction of its hidden layer by getting the information from input layer, to calculate the parameters in the output layer. The most commonly used ANNs in the field of SHM is back propagation (BP), categorized under the supervised learning algorithm.